Search research articles

Search research articles

Related Experiment Videos

Conformal self-organization for continuity on a feature map.

C Y. Liou¹, W P. Tai

¹Department of Computer Science and Information Engineering, National Taiwan University, 10764, Taipei, Taiwan

Neural Networks : the Official Journal of the International Neural Network Society

|March 29, 2003

Summary

This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same journal

Anchor-based disentanglement framework for incremental multi-view clustering.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Complex-valued amplitude-phase interference modeling for adversarially robust classification.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

TraNce: Type-aware hypergraph neural network with biological mediators for drug repositioning.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Decentralized ADMM for factorization-based Low-rank matrix estimation.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Memristive neuromorphic circuit design inspired by the neural mechanisms of conditioned fear.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Q-learning based asynchronous Boolean control networks stabilization with data loss.

Neural networks : the official journal of the International Neural Network Society·2026

See all related articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

This study introduces a self-organization model with conformal mapping for biological and geometric applications. It preserves topological conformality, enabling continuous exploration and mapping of input data for morphing.

Area of Science:

Computational geometry
Computational topology
Machine learning

Background:

Traditional self-organization models may not preserve topological properties.
Conformality is crucial in biological morphology and geometric surface mapping.

Purpose of the Study:

To develop and study a self-organization model incorporating conformal mapping.
To ensure topological conformality is preserved within the network field.
To facilitate continuous exploration and mapping of input data.

Main Methods:

Utilizing a self-organization model with a conformal-mapping adaptation.
Spanning a network field in the input space.
Preserving topological conformality during the process.

Related Experiment Videos

Main Results:

The converged network exhibits organized clustering of input features.
A specific mapping representation is generated by the model.
The model successfully explores input data in a continuous conformal sense.

Conclusions:

The proposed model effectively integrates conformal mapping into self-organization.
It meets the conformality requirements for biological and geometric applications.
The model's capabilities are demonstrated through simulations for morphing applications.